A Context-Aware Architecture for Realizing Business Process Adaptation Strategies Using Fuzzy Planning

Business competency emerges in flexibility and reliability of services that an enterprise provides. To reach that, executing business processes on a context-aware business process management suite which is equipped with monitoring, modeling and adaptation mechanisms and smart enough to react properly using adaptation strategies at runtime, are a major requisite. In this paper, a context-aware architecture is described to bring adaptation to common business process execution software. The architecture comes with the how-to-apply methodology and is established based on process standards like business process modeling notation (BPMN), business process execution language (BPEL), etc. It follows MAPE-K adaptation cycle in which the knowledge, specifically contextual information and their related semantic rules — as the input of adaptation unit — is modeled in our innovative context ontology, which is also extensible for domain-specific purposes. Furthermore, to support separation of concerns, we took apart event-driven adaptation requirements from process instances; these requirements are triggered based on ontology reasoning. Also, the architecture supports fuzzy-based planning and extensible adaptation realization mechanisms to face new or changing situations adequately. We characterized our work in comparison with related studies based on five key adaptation metrics and also evaluated it using an online learning management system case study.

Recognition of the Cybersecurity State of IoT devices

The identification of the cybersecurity (CS) state of Internet of things (IoT) devices determines the necessity to search for and improve approaches to detecting various threat types. The unification used in the mass development of IoT devices facilitates software and hardware modification to block certain built-in protective functions from the side of a potential intruder. A need arises to develop universal methods for identifying the cybersecurity state of devices using comprehensive approaches to analyzing data from internal and external information channels. The article presents an approach to identifying the cybersecurity of IoT devices based on processing time series recorded from sensors during various processes, and internal and external (thirdparty) sources. The approach is based on classification methods. The presented solution uses template sequences containing synchronized time series showing numerical values obtained from various probes and sensors during process execution. The proposed approach makes it possible to identify IoT device cybersecurity states without increasing the volume of information stored and processed in internal resources.

Which Event Happened First? Deferred Choice on Blockchain Using Oracles

First come, first served: Critical choices between alternative actions are often made based on events external to an organization, and reacting promptly to their occurrence can be a major advantage over the competition. In Business Process Management (BPM), such deferred choices can be expressed in process models, and they are an important aspect of process engines. Blockchain-based process execution approaches are no exception to this, but are severely limited by the inherent properties of the platform: The isolated environment prevents direct access to external entities and data, and the non-continual runtime based entirely on atomic transactions impedes the monitoring and detection of events. In this paper we provide an in-depth examination of the semantics of deferred choice, and transfer them to environments such as the blockchain. We introduce and compare several oracle architectures able to satisfy certain requirements, and show that they can be implemented using state-of-the-art blockchain technology.

Blockchain support for execution, monitoring and discovery of inter-organizational business processes

In an Inter-Organizational Business Process (IOBP), independent organizations (collaborators) exchange messages to perform business transactions. With process mining, the collaborators could know what they are actually doing from process execution data and take actions for improving the underlying business process. However, process mining assumes that the knowledge of the entire process is available, something that is difficult to achieve in IOBPs since process execution data generally is not shared among the collaborating entities due to regulations and confidentiality policies (exposure of customers’ data or business secrets). Additionally, there is an inherently lack-of-trust problem in IOBP as the collaborators are mutually untrusted and executed IOBP can be subject to dispute on counterfeiting actions. Recently, Blockchain has been suggested for IOBP execution management to mitigate the lack-of-trust problem. Independently, some works have suggested the use of Blockchain to support process mining tasks. In this paper, we study and address the problem of IOBP mining whose management and execution is supported by Blockchain. As contribution, we present an approach that takes advantage of Blockchain capabilities to tackle, at the same time, the lack-of-trust problem (management and execution) and confident execution data collection for process mining (discovery and conformance) of IOBPs. We present a method that (i) ensures the business rules for the correct execution and monitoring of the IOBP by collaborators, (ii) creates the event log, with data cleaning integrated, at the time the IOBP executes, and (iii) produces useful event log in XES and CSV format for the discovery and conformance checking tasks in process mining. By a set of experiments on real IOBPs, we validate our method and evaluate its impact in the resulting discovered models (fitness and precision metrics). Results revealed the effectiveness of our method to cope with both the lack-of-trust problem in IOBPs at the time that contributes to collect the data for process mining. Our method was implemented as a software tool available to the community as open-source code.

Facilitating Enhanced Decision Support Using a Social Norms Approach

Social norms constrain behavior of individuals either through obligating or prohibiting certain types of behavior. Norm-based mechanisms have only recently found applications in enhancing decisions of knowledge workers in an automated business process management context. The norms inferred in the context of business process executions are then recommended to users so as to enable them to make informed decisions. The previous work on prohibition norm inference focused on identifying failure cases, which is now complemented by first inferring norms from the successful process execution cases and then inferring prohibition norms. This approach based on considering social feedback (i.e. inferring what is obliged and prohibited from history logs of process execution) shows encouraging results under uncertain business environments. Using simulation results the paper demonstrates that using the norm based mechanism results in reduced failure rates in the decision making of a knowledge worker while still providing maximum flexibility for the user to choose from a range of actions to execute.

CHALLENGES OF USING LIVE PROCESS MIGRATION IN DISTRIBUTED EXASCALE SYSTEMS

Virtual machine-based process migrator mechanisms have the potential to be used in distributed exascale systems due to their ability to execute process execution and support environments with the heterogenous of the computational unit. The ability to reduce process suspension time and use the concept of live process migrator makes it possible to use this mechanism to transfer processes in distributed exascale systems to prevent related process activity failure. The performance function of a virtual machine-based process migrator mechanism cannot manage dynamic and interactive events and the effects of this event on the mechanism operation and the change in the basic concept of system activity from the concept of the process to the concept of global activity. This paper examines the challenges of dynamic and interactive event occurrence on virtual machine-based process migrators by analyzing VM-based migrator's performance function

Secure Data Transmission in BPEL (Business Process Execution Language)

In the world of computation, the encryption is a technique by which the plaintext or any type of data which is converted from the readable form is transformed into an encoded form. That encoded form can only be read by another entity if they have corrected key for decryption. The proposed technique providing the security to the data in inefficient way that can be further use in implementation in new upcoming task and enhancement in current running projects of SOA (Service Oriented Architecture) BPEL (Business Process Execution Language).